Are you leaving money on the table?

How using AI can improve pricing and grow profits

AI can help you work faster, hit the perfect price more often, and improve your win rates. Use it every time you price. Stop leaving money on the table.

As a manufacturer, you are familiar with investing in machinery to make more profit. Equipment improves and drives the market forward. Periodically, there are quantum leaps. The top machinery delivers the best quality, highest productivity and greatest versatility. Digitalisation takes over from skilled operators for tasks like setting, monitoring, and optimising. Those who invest generate the best profits and grow their business.

The same applies to pricing tools: AI is powering a quantum leap forward. Automating pricing calculations is a reality. With this comes improvements in quality and progressive refinement like your manufacturing processes.

Automated pricing defined

Collect customer requirements, and the AI will calculate the optimal price.

There is no need for expert input. The system checks parameters and optimises routing. Include all relevant factors and ensure quality.

Calculating an optimal price becomes a simple task completed in seconds by anyone.

What are the benefits?

Pricing is quick, increasing productivity in the commercial and sales departments.

Automating pricing codifies methods and captures activity and outcomes. This data feeds into future pricing to refine and improve.

Optimal price levels calculated fast mean more wins, especially in the merchant channel.

What does automating pricing involve?

Automation has three steps:
• Create an interface to collect what’s needed without conversational clarifications.
• Codify pricing steps, including ‘judgmental’ inputs, and establish a repeatable method. Optimise with experience.
• Apply a processing engine that can manage the many possible situations.

What goes into pricing?

Businesses use information collected from internal records and calculations,market intelligence and people’s judgment.

Cost and capacity are the primary internal data points. Market conditions and specific competitors add useful external intelligence.

What about people’s judgment? We split this into two categories: conclusions and opinions. A conclusion is the result of using available information and reaching a decision. Automation replicates this process and reaches correct conclusions. Separating the facts from the emotional element reduces decision noise and improves outcomes.

What about costing?

The cost of production is almost always used in pricing. There are several ways of calculating cost. Some methods are cost plus, material plus activity or full absorption costing. We also see mixed or hybrid models.

Choosing a consistent method and refining it over time gives the best results.

Interested to learn more about using AI in pricing

At we have worked with manufacturers from large to small. We have experience in guiding the pricing journey from yesterday’s methods to tomorrow’s. We have the advanced technologies to handle the most complex manufacturing environments. Get in touch for an introductory conversation.

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